Software Engineer, Systems

Meta•Menlo Park, CA

1d•$183,997 - $257,000

About The Position

Meta is seeking a Software Engineer specializing in systems software to drive technical direction across large-scale infrastructure and platform engineering. The team builds the foundational runtime that powers containers and virtual machines across Meta’s compute fleet. Its host-level systems launch, manage, isolate, monitor, and terminate workloads, coordinating workload artifacts and compute resources while enforcing performance, reliability, security, and resource-isolation boundaries. The runtime operates at a critical layer between applications and underlying host infrastructure. The role focuses on defining architecture for large-scale systems software and improving the efficiency, reliability, and scalability of distributed infrastructure. Work spans Linux systems programming, container and virtual machine lifecycle management, resource control, workload isolation, performance, and fleet reliability. The broader platform provides a common foundation for deploying and operating services across Meta’s infrastructure.

Requirements

Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
8+ years of experience in systems software engineering, including the design and implementation of operating system interfaces, runtime environments, distributed infrastructure, or low-level platform services.

Nice To Haves

Experience adhering to and implementing responsible, ethical AI practices, such as risk assessment, bias mitigation, and quality and accuracy reviews.
Experience leading large-scale platform migrations or systems modernization efforts in high-availability production environments.
Demonstrated ability to integrate AI tools to optimize or redesign workflows and drive measurable impact, such as efficiency gains or quality improvements.
Demonstrated ongoing AI skill development, such as prompt/context engineering or agent orchestration, and keeping current with emerging AI technologies.
Experience with operating system internals such as scheduler design, memory subsystems, or kernel-userspace interfaces.
Experience with distributed systems consensus protocols such as Raft or Paxos, or with building highly available and fault-tolerant infrastructure.

Responsibilities

Define and drive the long-term technical vision and architecture for large-scale systems software, including platform services, runtime environments, and low-level infrastructure components.
Architect systems-level solutions that meet performance, reliability, and scalability requirements across distributed infrastructure serving billions of users.
Set and drive the technical direction for the container runtime and isolation stack.
Improve fleet-wide efficiency and reliability of container-based workloads through resource enforcement, noisy-neighbor isolation, and increased density at millions-of-servers scale.
Extend runtime and isolation primitives to support AI training and inference workloads, including accelerator isolation, large-memory and high-bandwidth jobs, and gang-scheduled work.
Partner with kernel, scheduler, capacity, and hardware teams on hardware-software co-design and multi-generational fleet transitions.
Mentor engineers, drive cross-team design reviews, and represent the team’s container strategy within the organization.